The Architecture of Rural Life: The Dangers of Dense Collective Efficacy for At-Risk Girls

Dense ties and acquaintanceship result in small communities that deal with issues on an individual, informal basis. When issues such as sexual assault arise, if a victim is willing to seek services, studies have found that rurality negatively impedes on this process. The current study takes place in a primarily rural state, representing social control mechanisms somewhat different from cityscapes. The project relies heavily on in-depth interviews from incarcerated girls and women, as well as contributions from community actors, to assess collective efficacy in rural communities, influence of gender dynamics, and the impact on at-risk girls. Tracing participants' community roots, the study gathers structural and cultural characteristics of the locale, assessing social control practices as reported by local professionals. Results challenge literature proclaiming solely positive results from high levels of collective efficacy, finding that strong collective efficacy in nonurban areas gathers close insider ties, but “outsiders,” which includes girls identified in this research, are defined quickly and negatively, placing them in significant peril. Policy recommendations include broader cultural shifts coupled with local involvement with school personnel and church-involved patrons serving the needs of families and at-risk girls.     

Assessment of Catastrophic Risk Using Bayesian Network Constructed from Domain Knowledge and Spatial Data

Prediction of natural disasters and their consequences is difficult due to the uncertainties and complexity of multiple related factors. This article explores the use of domain knowledge and spatial data to construct a Bayesian network (BN) that facilitates the integration of multiple factors and quantification of uncertainties within a consistent system for assessment of catastrophic risk. A BN is chosen due to its advantages such as merging multiple source data and domain knowledge in a consistent system, learning from the data set, inference with missing data, and support of decision making. A key advantage of our methodology is the combination of domain knowledge and learning from the data to construct a robust network. To improve the assessment, we employ spatial data analysis and data mining to extend the training data set, select risk factors, and fine‐tune the network. Another major advantage of our methodology is the integration of an optimal discretizer, informative feature selector, learners, search strategies for local topologies, and Bayesian model averaging. These techniques all contribute to a robust prediction of risk probability of natural disasters. In the flood disaster's study, our methodology achieved a better probability of detection of high risk, a better precision, and a better ROC area compared with other methods, using both cross‐validation and prediction of catastrophic risk based on historic data. Our results suggest that BN is a good alternative for risk assessment and as a decision tool in the management of catastrophic risk.     

Essential Micro‐foundations for Contemporary Business Operations: Top Management Tangible Competencies,Relationship‐based Business Networks and Environmental Sustainability

Although various studies have emphasized linkages between firm competencies, networks and sustainability at organizational level, the links between top management tangible competencies (TMTCs) (e.g. contemporary relevant quantitative‐focused education such as big data analytics and data‐driven applications linked with the internet of things, relevant experience and analytical business applications), relationship‐based business networks (RBNs) and environmental sustainability have not been well established at micro‐level, and there is a literature gap in terms of investigating these relationships. This study examines these links based on the unique data collected from 175 top management representatives (chief executive officers and managing directors) working in food import and export firms headquartered in the UK and New Zealand. Our results from structural equation modelling indicate that TMTCs are the key determinants for building RBNs, mediating the correlation between TMTCs and environmental sustainability. Directly, the competencies also play a vital role towards environmental practices. The findings further depict that relationship‐oriented firms perform better compared to those which focus less on such networks. Consequently, our findings provide a deeper understanding of the micro‐foundations of environmental sustainability based on TMTCs rooted in the resource‐based view and RBNs entrenched in social network theory. We discuss the theoretical and practical implications of our findings, and we provide suggestions for future research.     

Risk Modeling, Assessment, and Management of Lahar Flow Threat

The 1991 eruption of Mount Pinatubo in the Philippines is considered one of the most violent and destructive volcanic activities in the 20th century. Lahar is the Indonesian term for volcanic ash, and lahar flows resulting from the massive amount of volcanic materials deposited on the mountain's slope posed continued post-eruption threats to the surrounding areas, destroying lives, homes, agricultural products, and infrastructures. Risks of lahar flows were identified immediately after the eruption, with scientific data provided by the Philippine Institute of Volcanology, the U.S. Geological Survey, and other research institutions. However, competing political, economic, and social agendas subordinated the importance of scientific information to policy making. Using systemic risk analysis and management, this article addresses the issues of multiple objectives and the effective integration of scientific techniques into the decision-making process. It provides a modeling framework for identifying, prioritizing, and evaluating policies for managing risk. The major considerations are: (1) applying a holistic approach to risk analysis through hierarchical holographic modeling, (2) applying statistical methods to gain insight into the problem of uncertainty in risk assessment, (3) using multiobjective trade-off analysis to address the issue of multiple decisionmakers and stakeholders in the decision-making process, (4) using the conditional expected value of extreme events to complement and supplement the expected value in quantifying risk, and (5) assessing the impacts of multistage decisions. Numerical examples based on ex post data are formulated to illustrate applications to various problems. The resulting framework from this study can serve as a general baseline model for assessing and managing risks of natural disasters, which the Philippines' lead agency-the National Disaster Coordinating Council (NDCC)-and other related organizations can use for their decision-making processes.     

Borrowing Information across Populations in Estimating Positive and Negative Predictive Values

A marker's capacity to predict risk of a disease depends on disease prevalence in the target population and its classification accuracy, i.e. its ability to discriminate diseased subjects from non-diseased subjects. The latter is often considered an intrinsic property of the marker; it is independent of disease prevalence and hence more likely to be similar across populations than risk prediction measures. In this paper, we are interested in evaluating the population-specific performance of a risk prediction marker in terms of positive predictive value (PPV) and negative predictive value (NPV) at given thresholds, when samples are available from the target population as well as from another population. A default strategy is to estimate PPV and NPV using samples from the target population only. However, when the marker's classification accuracy as characterized by a specific point on the receiver operating characteristics (ROC) curve is similar across populations, borrowing information across populations allows increased efficiency in estimating PPV and NPV. We develop estimators that optimally combine information across populations. We apply this methodology to a cross-sectional study where we evaluate PCA3 as a risk prediction marker for prostate cancer among subjects with or without previous negative biopsy.     

螺旋天线宽带阻抗匹配技术的研究

介绍了一种用渐变镜像传输线阻抗变换器来实现螺旋天线与50Ω馈线之间的宽带匹配技术.实验结果表明,采用渐变镜像传输线阻抗变换器能在2:1的频带范围内实现 ρ<2.     

中西方管理研究的整合

本评论在Barney和Zhang[1],及Whetten[2]深入透彻的分析基础上,提出了中国管理研究的发展方向。首先,中国管理研究者可以发展创新的及具有影响力的想法和理论,这些想法和理论并不一定局限于中国文化的背景,而可以是放诸四海而皆准的。这一方向成功的机率取决于所提出想法和理论的价值。另一途径是尝试融合,即"文化特殊性—文化普遍性"结合的方法,以整合西方及本土的理论的元素。最后一个方向是使用协同方法实现西方及本土理论之间的动态互动,并最终发展出创新的、具有文化普遍适用性的理论。本文建议华人管理研究应该同时重视这三种思路。     

基于Windows2000远程教育平台的开发和建设

近年来,随着计算机网络技术的飞速发展,国内外都在大力开发和推广基于internet的远程教育技术,这种教育系统以多媒体应用程序为基础,通过计算机网络将教师的图像,声音,作业传送给学生,通过实时或非实时来实现。本文介绍怎样利用Windows2000中的多媒体应用程序来搭建适合于远程教育的应用平台。